kubernetes
Kubernetes HPA Generator
Generate a Kubernetes HorizontalPodAutoscaler manifest targeting CPU and/or memory utilisation. Supports custom metrics and scale-down stabilisation.
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Kubernetes HorizontalPodAutoscaler
HPA continuously watches pod metrics and adjusts the replica count of a Deployment (or StatefulSet) to match a target utilisation.
How it works
desired_replicas = ceil(current_replicas × (current_metric / target_metric))If 3 pods are running at 90% CPU and target is 70%: desired = ceil(3 × 90/70) = ceil(3.86) = 4 pods
Scale-up vs scale-down
| Scale-up | Scale-down | |
|---|---|---|
| Default period | 15s | 300s stabilisation window |
| Behaviour | Aggressive | Conservative |
| Why | Avoid overload | Avoid thrashing |
Custom metrics (KEDA)
For queue depth, request rate, or external metrics, consider KEDA (Kubernetes Event-Driven Autoscaler):
apiVersion: keda.sh/v1alpha1
kind: ScaledObject
spec:
triggers:
- type: prometheus
metadata:
query: sum(rate(http_requests_total[2m]))
threshold: "100"Prerequisites
# Install metrics-server (required for CPU/memory HPA)
kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml# Verify kubectl top pods kubectl top nodes ```
Key Terms
Full glossary →kubeadm
A tool for bootstrapping Kubernetes clusters. It automates the setup of control plane components and joining worker nodes, following Kubernetes best practices.
etcd
A distributed key-value store used by Kubernetes to store all cluster state and configuration. etcd is the single source of truth for the entire cluster.
cert-manager
A Kubernetes controller for automating TLS certificate management. cert-manager can issue certificates from Let's Encrypt, Vault, or internal CAs, and automatically renews them.
Helm
A package manager for Kubernetes. Helm charts bundle Kubernetes manifests into reusable packages with configurable values, versioned and published to chart repositories.
Frequently Asked Questions
What's the difference between HPA and VPA?
HPA (HorizontalPodAutoscaler) adds more pod replicas. VPA (VerticalPodAutoscaler) adjusts the CPU/memory requests of existing pods. HPA is for stateless apps; VPA is useful for single-replica stateful workloads or when you can't scale horizontally. They can be used together but need careful configuration to avoid conflicts.
Why does HPA need metrics-server?
HPA reads resource metrics (CPU, memory) via the Kubernetes metrics API, which is provided by metrics-server. Without it, HPA cannot observe utilisation and will not scale. Install it with: kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml
What does the stabilisation window prevent?
Without a scale-down stabilisation window, HPA might scale down too aggressively after a short traffic spike — then scale back up again when traffic returns, causing thrashing. The default 300s window means HPA waits 5 minutes of consistently low load before reducing replicas.
What's a good CPU target percentage?
70% is a common starting point — it leaves 30% headroom before a pod is CPU-saturated while still triggering scale-out early enough. Setting it too high (>85%) means you scale out too late and requests queue. Too low (<50%) means you waste compute on pods that are mostly idle.
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